13 November 2003 Wavelet domain blind image separation
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Abstract
In this work, we consider the problem of blind source separation in the wavelet domain via a Bayesian estimation framework. We use the sparsity and multiresolution properties of the wavelet coefficients to model their distribution by heavy tailed prior probability laws: the generalized exponential family and the Gaussian mixture family. Appropriate MCMC algorithms are developed in each case for the estimation purposes and simulation results are presented for comparaison.
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Mahieddine M. Ichir, Mahieddine M. Ichir, Ali Mohammad-Djafari, Ali Mohammad-Djafari, } "Wavelet domain blind image separation", Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); doi: 10.1117/12.508134; https://doi.org/10.1117/12.508134
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